{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T04:44:23Z","timestamp":1777697063477,"version":"3.51.4"},"reference-count":34,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T00:00:00Z","timestamp":1759795200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Intelligent Decision Technologies"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:p>In recent days, skeletal bone age assessment gained more attention from researchers for auxiliary diagnosis and prediction in medical issues. Hence, it is essential to undertake more than a few complications existing in the traditional techniques in order to enhance the age assessment efficiency. So, this research work presented an intellectual skeletal bone age estimation method with neural network learning. At first, the needed images are gathered as of the available online source. Further, from gathered images, three sets of features are extracted from Vision Transformer (ViT) features as F1, Local Weber Pattern (LWP) image as F2, and raw image as F3. Subsequently, the resultant features are fed into the Vision Transformer-based Multi-scale MobileNet (ViT-MMNet) designed for assessing a skeletal bone age. In this network, multi-scale MobileNet is considered to execute the prediction process, where the ViT-based features are given to the first convolution layer, LWP-based features are given to the second convolution layer, and finally, in third convolution layer, the original images collected from the datasets are directly given. Finally, detailed experimental validations are conducted for the designed skeletal bone age assessment framework through traditional methods to assure the efficacy of the method.<\/jats:p>","DOI":"10.1177\/18724981251382482","type":"journal-article","created":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T15:51:51Z","timestamp":1759852311000},"page":"4025-4046","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Design and development of vision transformer-based multi-scale MobileNet for skeletal bone age assessment with image features"],"prefix":"10.1177","volume":"19","author":[{"given":"Yellapu Vineela","family":"Sravya","sequence":"first","affiliation":[{"name":"Gandhi Institute of Technology and Management (Deemed to be University)"}]},{"given":"Rita","family":"Roy","sequence":"additional","affiliation":[{"name":"Gandhi Institute of Technology and Management (Deemed to be University)"}]},{"given":"Gorla","family":"Srinivas","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, ANIL Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India"}]}],"member":"179","published-online":{"date-parts":[[2025,10,7]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3074713"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-08943-1"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00247-023-05789-1"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13534-020-00151-y"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00247-019-04587-y"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-021-10935-8"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.2020190198"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106456"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.3390\/app10207233"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3218574"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8460493"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101743"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2021.3095128"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001423540010"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00247-022-05295-w"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105083"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2023.08.030"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.01.057"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3358821"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3108219"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2020.105754"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.10.032"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103016"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-021-00376-z"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-020-02266-0"},{"key":"e_1_3_2_27_2","volume-title":"Efficient and gender-adaptive graph vision mamba for pediatric bone age assessmentInternational conference on medical image computing and computer-assisted intervention","author":"Zhou L","year":"2024","unstructured":"Zhou L, Yi Z, Zhou K, et\u00a0al. Efficient and gender-adaptive graph vision mamba for pediatric bone age assessment. International conference on medical image computing and computer-assisted intervention. Cham: Springer Nature Switzerland, 2024."},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.legalmed.2023.102362"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.131299"},{"key":"e_1_3_2_30_2","first-page":"357","article-title":"CrossViT: cross-attention multi-scale vision transformer for image prediction","author":"Chen C-F","year":"2021","unstructured":"Chen C-F, Fan Q, Panda R. CrossViT: cross-attention multi-scale vision transformer for image prediction. Computer Vision and Pattern Recognition 2021: 357\u2013366.","journal-title":"Computer Vision and Pattern Recognition"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2025.05.090"},{"key":"e_1_3_2_32_2","first-page":"271","article-title":"AE-BoNet: a deep learning method for pediatric bone age estimation using an unsupervised Pre-trained model","volume":"15","author":"Sirati-Amsheh M","year":"2025","unstructured":"Sirati-Amsheh M, Shabaninia E, Chaparian A. AE-BoNet: a deep learning method for pediatric bone age estimation using an unsupervised Pre-trained model. J Biomed Phys Engineering 2025; 15: 271\u2013280.","journal-title":"J Biomed Phys Engineering"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125160"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102971"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3065195"}],"container-title":["Intelligent Decision Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18724981251382482","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/18724981251382482","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18724981251382482","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:21:45Z","timestamp":1777454505000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/18724981251382482"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,7]]},"references-count":34,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["10.1177\/18724981251382482"],"URL":"https:\/\/doi.org\/10.1177\/18724981251382482","relation":{},"ISSN":["1872-4981","1875-8843"],"issn-type":[{"value":"1872-4981","type":"print"},{"value":"1875-8843","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,7]]}}}